Barriers to Optimal Clinician Guideline Adherence in Management of Markedly Elevated Blood Pressure

This qualitative analysis uses electronic health record data to analyze barriers to clinician adherence to clinical guidelines for managing severe hypertension.


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Introduction
Hypertension is a major public health issue, affecting almost one-half of the US adult population.
Among patients with hypertension, those with severely elevated blood pressure (BP; defined as at least 2 consecutive readings of systolic BP Ն160 mm Hg or diastolic BP Ն100 mm Hg) comprise about 12% 1,2 and face a higher risk of complications, including severe and rapid systemic end-organ damage, compared with those with modestly elevated BP. 3 This condition requires prompt and appropriate pharmacological treatment.The 2017 American College of Cardiology and American Heart Association guidelines 3 recommend immediate evaluation and drug treatment followed by careful monitoring and dose adjustments for patients with severe hypertension.Despite these wellestablished clinical practice guidelines, clinician adherence remains suboptimal.A recent study 4 based on electronic health record (EHR) data in the ambulatory setting found that almost 30% of patients with severely elevated BP had no active antihypertensive drug prescription before their second visit, and only 54% of those who were prescribed at least 1 antihypertensive drug class were prescribed the guideline-recommended 2-drug class combination therapy.This finding highlights a missed opportunity to improve guideline adherence in this population.
Clinicians' adherence to medication guidelines is a complex and multifaceted process that substantially impacts the implementation of evidence-based practice. 5The literature highlights various scenarios resulting in nonadherence to medication guidelines.These scenarios include situations where the recorded BP does not accurately reflect the patient's typical BP, such as when home BPs are below the target range or when the patient is experiencing pain. 6In addition, scenarios such as the prioritization of other clinical concerns over hypertension, the need for ongoing monitoring and lifestyle counseling, and disagreements with specific recommendations, also result in nonadherence. 6Moreover, how clinicians address patient-level factors, such as medication nonadherence and individual patient preferences, substantially influences guideline adherence.
Clinician-level factors, including the belief that hypertension management is another clinician's responsibility, further impact guideline adherence.Medication-related issues, such as adverse drug events and use of medications from external sources, present additional adherence challenges. 6By recognizing and addressing these multifaceted factors, health care systems can implement strategies to improve clinician adherence to medication guidelines and enhance patient outcomes.However, the current body of research on clinician guideline adherence in managing markedly elevated BP lacks a comprehensive identification of the reasons behind the inadequate treatment, particularly those based on routinely collected information during clinical practice, such as data from medical records.This information is particularly crucial as pharmacological interventions are vital in reducing BP and associated complications for this patient population.Furthermore, previous studies may have inadequately reported or underrepresented barriers to clinician guideline adherence, potentially due to methodological limitations. 5Consequently, we aimed to address these gaps by conducting a content analysis of EHRs to develop a comprehensive taxonomy of scenarios representing suboptimal guideline adherence in the ambulatory management of severe hypertension.This information can potentially guide the creation and implementation of focused interventions, enhancing adherence to guidelines and quality of care for severe hypertension.
Moreover, because the information is derived from EHR data, it is pragmatic and enables the development of practical, automated EHR-based clinical decision support tools. 7

Data Sources
This qualitative study was approved by the institutional review board at Yale University and the need for informed consent was waived.This study was reported according to the Standards for Reporting Qualitative Research (SRQR) reporting guideline. 8The dataset included data from adult patients at Yale New Haven Health System (YNHHS) who had at least 2 consecutive outpatient visits between

Study Population
Eligible patients were aged 18 to 85 years and had markedly elevated BP, defined as having measurements of systolic BP of 160 mm Hg or greater or diastolic BP of 100 mm Hg or greater in at least 2 consecutive outpatient visits between January 1, 2013, and December 31, 2021, with no new antihypertensive medication prescription within 90 days of the index date.The index date was defined as the date of the second severely elevated BP reading.Patients with markedly elevated BP were selected as a focus given that the need to urgently achieve BP control in this population is unequivocal.Any 2 consecutive visits were required to be at least 1 day apart.We had access to all available data in the medical records, including patient demographics, past medical histories, vital signs, outpatient medications, laboratory results, encounter notes and scanned documents.Of note, identification of patient race and ethnicity was conducted using data extracted from the EHR.This data was classified based on information provided directly by the patients themselves, either through self-report at the time of registration or during patient intake processes.The specific categories for race included in our study were Black, White, and other (defined as any race not otherwise specified), while ethnicity is categorized as Hispanic or Latino, non-Hispanic, and other (defined as any ethnicity not otherwise specified).A total of 20 654 patients met the eligibility criteria (eFigure in Supplement 1).We randomly selected 200 records from the group of all eligible patients for qualitative analysis, intending to select more if we did not achieve saturation (where no new concepts emerged from analyses of subsequent data 9 ).

Approach to Thematic Analysis and Taxonomy Development
Using a previously published inductive, systematic approach, [10][11][12][13][14] we conducted a thematic analysis of EHR data to generate a pragmatic taxonomy of suboptimal clinician guideline adherence scenarios in managing severe hypertension.

Step 1: Development of Rubric for Medical Record Review
Through an iterative process, a team of 3 clinicians and/or experienced cardiovascular researchers (O.A., Y.L., and H.M.K.) developed a rubric to systematically abstract data from the EHR.We obtained demographic data (including age, sex, race, and ethnicity) and clinical data relevant to the diagnosis and treatment of hypertension (including BP measurements, medical history, medication prescriptions, and medical context of the encounter) and established criteria for consistency (to support explicit review).Additionally, the data extraction rubric was designed to offer flexibility, allowing reviewers to go beyond strict numerical or binary criteria and make subjective assessments.
This approach included evaluating the rationale behind a clinician's decisions, considering the medical context of each encounter, and interpreting data points with a nuanced understanding of patient history, comorbidities, or unique clinical scenarios.[16][17] Step 2: Data Abstraction Two abstractors (O.A. and X.Q.) participated in a training session, during which they collectively abstracted 15 medical records using the rubric and generated a narrative summary for each case.discussion among all reviewers until consensus was reached.Once the rubric was finalized, each abstractor reviewed a random sample of 50 medical records.Cases were reviewed until reviewers determined they reached saturation; that is, no new constructs emerged from reviewing subsequent cases. 9Specifically, when reviewers felt they reached saturation, they reviewed another 10 charts to confirm no further constructs were identified.
Step 3: Content Analysis and Taxonomy Development The cases abstracted using the rubric were analyzed using conventional content analysis.Content analysis is a systematic, replicable technique for compressing many words of text into fewer content categories based on explicit coding rules. 18,19Content analysis enables researchers to sift through large volumes of data with relative ease in a systematic fashion, and it is useful in examining the patterns in documentation. 20

Data Analysis
The thematic analysis and qualitative data were analyzed using NVIVO software version 12.0 (QSR International).The analysis was conducted from January to December 2023.

Study Sample Characteristics
Thematic saturation was reached after analyzing 100 patients.

Content Domains
Based on a thematic analysis of data available in the EHR for patients meeting our criteria, we identified a variety of scenarios of suboptimal clinician guideline adherence in managing severe hypertension pertaining to either noninitiation or nonintensification of pharmacological therapy (Table 2).Noninitiation of pharmacological treatment was defined as an absence of the initiation of antihypertensive therapy in response to severely elevated BP in a patient with at least 2 consecutive readings of severely elevated BP.Nonintensification of pharmacological treatment was defined as failure to intensify or modify treatment or initiate an urgent referral on the index visit for a patient with severely elevated BP who was previously taking antihypertensive medication.

Clinician-Related Scenarios
Clinician-related scenarios were defined as instances where clinicians did not initiate or intensify antihypertensive treatment due to factors related to their intentions, capabilities, or scope.Under explicitly displacing responsibility to a hypertension-managing clinician (ie, primary care physician or cardiology), excluding cases where an urgent referral to the clinician was made.For example, our analysis identified a case where a patient had a visit with a podiatrist and exhibited markedly elevated blood pressure.The podiatrist noted that the patient needed to see their primary care physician, but no follow-up occurred.

Maintenance of current BP intervention
The clinician did not initiate or intensify treatment due to variations in BP measurements, whether at home or in the office.This includes cases where high in-office readings were believed to be a result of the white coat effect, pain, or other causes of reactive elevated BP.
Clinician chose to delay intensifying treatment to observe if current antihypertensives/lifestyle modifications would result in BP control.

Clinician did not intensify treatment due to competing clinical considerations
Clinician did not intensify intervention due to patient's nonadherence to current therapy.
Clinician did not initiate/intensify intervention due to patient preference not to.
Clinician did not acknowledge nor prioritize the BP at visit.Specialist visit did not initiate/intensify treatment, opting instead to defer responsibility to a hypertensionmanaging clinician (eg, PCP, cardiologist), excluding cases where an urgent referral to said clinician was made.

Main content domain Subcategory Description
BP indicates blood pressure; PCP, primary care physician.Patient nonadherence included instances where the clinician did not intensify intervention due to the patient's nonadherence to current therapy.For example, our analysis identified a case in which a patient who had previously had adequate BP control while taking metoprolol had not taken his medication in 2 days when he presented with markedly elevated BP and the clinician decided to counsel the patient on adherence rather than modify or intensify treatment at the visit (Table 3).

JAMA Network Open | Cardiology
Patient preference included instances where the clinician did not initiate nor intensify intervention due to patient preference.

Clinical Complexity-Related Scenarios
These scenarios involve instances where clinicians did not initiate or intensify antihypertensive treatment due to the complexities of the clinical situation.Under this main content domain, we  3).For example, our analysis identified a case where a patient had substantial kidney injury, and the physician decided not to treat the patient's hypertension due to the kidney condition

Discussion
This qualitative study provides novel insights into the factors contributing to suboptimal adherence to guidelines among clinicians treating patients with markedly elevated BP in ambulatory settings.
Our taxonomy, derived from EHR data, not only categorizes these instances but also describes the  Our findings underscore the necessity of addressing the multidimensional nature of guideline nonadherence.Under the proposed taxonomy, each category and subcategory of nonadherence scenarios is linked to specific factors and targeted interventions.7][28] Health organizations can further support clinician adherence by integrating evidence-based decision support tools within EHR systems, such as automated alerts, reminders, and advanced patient portals, along with improved collaborative tools for care teams. 29dressing health professional-level factors involves fostering a willingness to embrace new practices, educating about guidelines, and reinforcing personal accountability. 7,30For patient-level factors, strategies include raising health awareness, early education, clear communication about the impact of nonadherence, and peer support.Concerning the guidelines themselves, simplifying their presentation, tailoring them to the local context, and involving end-users in their development can enhance their usability and adherence. 7,31flecting on the broader implications, this study's findings can stimulate health care policies aimed at systematizing adherence to guidelines and, thus, improve the quality of care delivered.This is particularly pertinent in light of our identification of implicit bias and structural racism as underlying factors contributing to nonadherence, which are critical to address in the pursuit of equitable health care. 32,33

Findings
In this qualitative study of 100 patients with markedly elevated blood pressure, 3 domains of suboptimal adherence were developed (clinicianrelated scenarios, patient-related scenarios, and clinical complexityrelated scenarios) and several plausible contributing factors were identified, including a lack of clear protocols and processes to implement guidelines, infrastructure limitations, clinicians' lack of autonomy and authority, excessive workload, time constraints, and clinician belief or perception.Meaning This study introduced a taxonomy poised to inform targeted interventions, thereby enhancing guideline adherence and elevating care quality for severe hypertension.

Figure .
Figure.Taxonomy of Scenarios of Suboptimal Clinician Guideline Adherence in the Management of Severe Hypertension

identified 3
subcategories: diagnostic uncertainty with BP measurement, maintenance of current BP intervention, and competing medical priorities (Figure).Diagnostic uncertainty with BP measurement included cases where the clinician did not initiate or intensify treatment due to variation in BP measurements, either at home or in the office.It also reflected situations where clinic BP measurements contradicted home measurements, thus creating uncertainty in determining the true hypertensive status of the patient.Maintenance of current BP intervention included cases where the clinician chose to delay intensifying treatment to observe if current antihypertensives and/or lifestyle modifications would result in BP control.Competing medical priorities included cases in which the clinician chose to delay intensifying treatment due to several competing medical conditions (Table role misperceptions can also play a part, alongside unclear guidelines.Patient-related barriers, like nonadherence or preference, might arise from clinician reluctance influenced by patient characteristics, clinician beliefs, fear of complications, and patient unawareness or demotivation.Perceptions of guideline inflexibility also contribute to these barriers.Clinical complexity scenarios, including diagnostic uncertainty, maintenance of interventions, and competing priorities, are affected by organizational issues, reliance on clinical experience over guidelines, patient comorbidities, and guideline perceptions restricting clinical judgment and autonomy.
Barriers to Clinician Guideline Adherence in Management of Severe Hypertension used emergent coding and established categories following a preliminary examination of the abstracted data obtained in step 2. First, 1 author (O.A.) independently reviewed the abstracted data and identified a set of suboptimal clinician guideline adherence scenarios to form the initial code list, which was then developed into a consolidated code book.Second, 2 authors (O.A. and Y.L.) 21viewed this code book for face validity and revised it based on group discussion.Third, the consolidated code book was trialed on 10 cases by the coding group (O.A. and Y.L.) to ensure consistent coding application.The coding group checked that the reliability of the coding was established (agreement >95%).Then all cases were coded by the coding group.Finally, a larger author group (O.A., Y.L., L.C., and H.M.K.) used an iterative, consensus-based discussion process to group the coding into major content themes with subthemes, maintaining a consensus and primary data referencing approach.21 Barriers to Clinician Guideline Adherence in Management of Severe Hypertension These identified scenarios (subcategories) of suboptimal clinician guideline adherence were taxonomized and grouped into 3 main content domains: clinician-related scenarios, patient-related scenarios, and clinical complexity-related scenarios (Figure).Table3includes example quotations or clinical situations pertaining to each scenario.

Table 1 .
Demographics of 100 Patients Included in the Sample for Qualitative Content Analysis Did not address included instances in which the clinician encountered on the index date neither acknowledged nor prioritized the BP at the visit.For example, Table3highlights a clinical scenario in which a patient who presented to a clinician for wound care had a second consecutive markedly elevated BP reading at presentation, but this was not addressed in the encounter note, nor was any action or intervention relating to the BP carried out.Diffusion of responsibility included instances in which the specialist visited did not initiate or intensify treatment, a Other race and ethnicity were defined as any race or ethnicity not otherwise specified.bBodymassindex was calculated as weight in kilograms divided by height in meters squared.JAMA Network Open | CardiologyBarriers to Clinician Guideline Adherence in Management of Severe Hypertension JAMA Network Open.2024;7(8):e2426135.doi:10.1001/jamanetworkopen.2024.26135(Reprinted) August 6, 2024 5/11 Downloaded from jamanetwork.comby guest on 08/08/2024 this main content domain, we identified 2 subcategories: did not address and diffusion of responsibility (Figure).

Table 2 .
Scenarios of Suboptimal Clinician Guideline Adherence in the Management of Severe Hypertension Identified Under Noninitiation or Nonintensification of Antihypertensive Treatment (Order of Frequency From Most to Least) Barriers to Clinician Guideline Adherence in Management of Severe Hypertension Patient-related scenarios were defined as instances where clinicians did not initiate or intensify antihypertensive treatment due to considerations related to patient behavior.Under this main content domain, we identified 2 subcategories: patient nonadherence and preference(Figure).

Table 3 .
5,24,25 Quotations and Clinical Situations Illustrating Clinician-Related, Patient-Related, and Clinical Complexity-Related Scenarios factors influencing each scenario of suboptimal adherence.Such a pragmatic framework is poised to inform targeted interventions, thus enhancing adherence and patient outcomes.Our study advances the existing body of literature in several ways.We have previously detailed various mechanisms through which patients experience persistent hypertension, such as the lack of intensification in pharmacological treatment, failure to implement prescribed therapies, and nonresponse to treatment.11Buildingonthis,thecurrentstudyspecificallyilluminatesthe mechanisms behind clinicians' failure to treat ambulatory patients with severely elevated BP effectively and explores the reasons for these shortcomings.To our knowledge, this is the first study to develop a taxonomy for categorizing instances of suboptimal clinician adherence to guidelines in managing patients with markedly elevated BP using clinical data.Compared with prior work on clinical inertia,22,23a key strength of this study is its foundation in EHR data.EHRs capture a broad spectrum of clinical interactions across diverse patient demographics, enhancing our findings' practicality and external validity.7ResearchbasedonEHRdata can inform more effective clinical decisions by evaluating the quality and cost implications of guideline-conformant care for chronic conditions such as hypertension.Furthermore, EHRs assist in pinpointing the issue of suboptimal clinician guideline adherence in the management of substantially elevated BP and serve as a robust framework for integrating potential EHR-based solutions such as decision support tools.Various influencing factors were hypothesized for each taxonomized scenario of suboptimal clinician adherence to guidelines in managing severe hypertension.These factors, frequently reported in the literature,5,24,25span health organization, health professional, patient, and guideline contexts.In clinician-related scenarios (eg, did not address and diffusion of responsibility) barriers JAMA Network Open.2024;7(8):e2426135.doi:10.1001/jamanetworkopen.2024.26135(Reprinted) August 6, 2024 7/11 Downloaded from jamanetwork.comby guest on 08/08/2024 may include unclear institutional roles, insufficient consultation time, excessive workload, and infrastructure limitations (eTable in Supplement 1).Factors such as clinician autonomy, authority, or